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Record W2124725715 · doi:10.7202/037413ar

Traduire les Antilles en anglais : trahir ou fêter la polyphonie?

2007· article· fr· W2124725715 on OpenAlexvenueno aff
Valérie Budig-Markin, Martha Manier

Bibliographic record

VenueTTR traduction terminologie rédaction · 2007
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Traduire les Antilles en anglais : Trahir ou fêter la polyphonie? — Les rapports complexes de langue-culture aux Antilles, lorsqu'on les traduit du français vers l'anglais, se situent sur les plans culturel, naturel et créole-francais. Quand on traduit l'espagnol de Porto Rico en anglais, il s'agit surtout de problèmes d'emprunts, de transfert et de code switching anglais-espagnol dans l'original. Dans les deux cas, par contre, la même question se pose pour le traducteur : comment fêter la polyphonie sans la trahir? Nous examinons quatre nouvelles martiniquaises et portoricaines et leur unicité de contexte pour offrir des solutions spécifiques, des expressions exemplaires, des textes et contextes problématiques, et aussi pour signaler certains problèmes difficiles que pose la traduction des Antilles.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.015
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.070
GPT teacher head0.360
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2007
Admission routes1
Has abstractyes

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